Early Detection of Hardware Trojans Using Neural Controlled Differential Equations and Analysis of Power Traces

Evolving Hardware Trojans pose a serious threat to modern digital systems by evading traditional detection through stealthy, adaptive behavior. Even recent methods that leverage advances in machine learning can only detect them after activation, leaving a critical window for potential security...

Scalable Malware Family Classification Using Quantum Kernel Based Machine Learning

The classification of malware families is a key challenge in cybersecurity, which enables threat attribution, analysis of attack operations, and the formulation of effective defense strategies. Emerging malware samples are becoming increasingly structurally similar and obfuscated, making accurate...

Machine Learning Power Side-Channel Attack on SNOW-V

This paper demonstrates a power analysis-based Side-Channel Analysis SCA attack on the SNOW-V encryption algorithm, which is a 5G mobile communication security standard candidate. Implemented on an STM32 microcontroller, power traces captured with a ChipWhisperer board were analyzed, with Test...